{"title":"UINT: An intent-based adaptive routing architecture","authors":"Huijie Ma , Yuxiang Ma , Yulei Wu","doi":"10.1016/j.comnet.2024.110991","DOIUrl":null,"url":null,"abstract":"<div><div>The exponential growth of smart devices and network scale has led to a rapid increase in network traffic, posing severe challenges to network resource utilisation and transmission efficiency. Intent-based networking (IBN) provides a high-level, automated method for network management. It dramatically simplifies network operations and enhances network flexibility and manageability. However, existing studies mainly focus on applying IBN in certain stages of network management without fully leveraging IBN’s network awareness and automated deployment features to comprehensively optimise network management and traffic forwarding. We propose an architecture for optimising network traffic based on user intents, i.e., UINT, which aims to simplify network management and optimise network traffic forwarding to enhance the Quality of Service (QoS) for end users. The proposed UINT leverages IBN’s automated sensing capabilities to perceive end device users’ network intents, proactively formulating adaptive network traffic forwarding strategies and deploying these strategies to switches before the user’s requested network traffic arrives. When the traffic user requests arrive, it directly matches the flow table for forwarding, eliminating any waiting time. UINT considers the differences in QoS requirements of various traffic and adjusts the traffic forwarding strategy based on network conditions, providing new perspectives and methods for formulating network traffic forwarding strategies. We verify the effectiveness and reliability of UINT in various network environments through experiments. Extensive evaluation experiments indicate the UINT predictor’s effectiveness and the efficacy of its adaptive routing algorithm and dynamic adjustment mechanism in optimising network traffic latency, throughput, and bandwidth.</div></div>","PeriodicalId":50637,"journal":{"name":"Computer Networks","volume":"257 ","pages":"Article 110991"},"PeriodicalIF":4.4000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Networks","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1389128624008235","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0
Abstract
The exponential growth of smart devices and network scale has led to a rapid increase in network traffic, posing severe challenges to network resource utilisation and transmission efficiency. Intent-based networking (IBN) provides a high-level, automated method for network management. It dramatically simplifies network operations and enhances network flexibility and manageability. However, existing studies mainly focus on applying IBN in certain stages of network management without fully leveraging IBN’s network awareness and automated deployment features to comprehensively optimise network management and traffic forwarding. We propose an architecture for optimising network traffic based on user intents, i.e., UINT, which aims to simplify network management and optimise network traffic forwarding to enhance the Quality of Service (QoS) for end users. The proposed UINT leverages IBN’s automated sensing capabilities to perceive end device users’ network intents, proactively formulating adaptive network traffic forwarding strategies and deploying these strategies to switches before the user’s requested network traffic arrives. When the traffic user requests arrive, it directly matches the flow table for forwarding, eliminating any waiting time. UINT considers the differences in QoS requirements of various traffic and adjusts the traffic forwarding strategy based on network conditions, providing new perspectives and methods for formulating network traffic forwarding strategies. We verify the effectiveness and reliability of UINT in various network environments through experiments. Extensive evaluation experiments indicate the UINT predictor’s effectiveness and the efficacy of its adaptive routing algorithm and dynamic adjustment mechanism in optimising network traffic latency, throughput, and bandwidth.
期刊介绍:
Computer Networks is an international, archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in the computer communications networking area. The audience includes researchers, managers and operators of networks as well as designers and implementors. The Editorial Board will consider any material for publication that is of interest to those groups.